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2023 International Conference on Frontiers of robotics and Software Engineering, FRSE 2023

作者： Ju, Fengjia Jin, Hongzhe Zhao, Jie Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350301113

The mobile humanoid upper body robot combines the humanoid upper body robot with the mobile platform. It has high redundancy and can complete complex tasks. However, coupling joints, including the waist joints and the mobile platform, exist in the configuration of the robot. During the task execution, the motion of the end-effectors on the dual arms are not independent, but interfere with each other through the motion of the waist and the mobile platform. Therefore, we need to decouple the waist and mobile platform from the dual arms. Based on the pseudo-inverse method of the redundant manipulators, we consider the motion of the coupling joints as a disturbance term and propose a kinematic decoupling whole-body control method. The method realizes the decoupling and cooperation of dual arms, avoids the interference of the inverse kinematics model of the dual arms, and fully releases the application potential of the high redundancy. The decoupling method allows the waist joints and the mobile platform to move randomly without affecting the task operation at the end-effectors, and to further plan their movements separately in order to smooth the whole body motion. The simulations on the mobile humanoid upper body robot verifies our method. © 2023 IEEE.

关键词： End effectors

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Dynamic compliance of energy-saving legged elastic parallel joints for quadruped robots:design and realization

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Frontiers of Mechanical Engineering 2024年第2期19卷 45-58页

作者： Yaguang ZHU Minghuan ZHANG Xiaoyu ZHANG Haipeng QIN Key Laboratory of Road Construction Technology and Equipment of Ministry of Education School of Engineering MachineryChang’an UniversityXi’an 710064China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China

Achieving dynamic compliance for energy-efficient legged robot motion is a longstanding *** recent predictive control methods based on single-rigid-body models can generate dynamic motion,they all assume infinite energy,making them unsuitable for prolonged robot *** this issue necessitates a mechanical structure with energy storage and a dynamic control strategy that incorporates feedback to ensure *** work draws inspiration from the efficiency of bio-inspired muscle–tendon networks and proposes a controllable torsion spring leg *** design integrates a spring-loaded inverted pendulum model and adopts feedback delays and yield springs to enhance the delay effects.A leg control model that incorporates motor loads is developed to validate the response and dynamic performance of a leg with elastic *** model provides torque to the knee joint,effectively reducing the robot’s energy consumption through active or passive control *** benefits of the proposed approach in agile maneuvering of quadruped robot legs in a realistic scenario are demonstrated to validate the dynamic motion performance of the leg with elastic joints with the advantage of energy-efficient legs.

关键词： dynamic responsiveness energy dissipation legged locomotion parallel joints quadruped robot

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High accuracy target point classification through dark-field detection of large-aperture optics surface based on machine vision

High accuracy target point classification through dark-field...

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2024 Applied Optics and Photonics China: Optical Sensing, Imaging technology, and Applications, AOPC 2024

作者： Zhou, Shicheng Yin, Zhaoyang Wang, Bei Zhao, Linjie Cheng, Jian Chen, Mingjun School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

ISBN: (数字)9781510687820

ISBN: (纸本)9781510687813

Surface defects on optics seriously affect their service life in high-power laser system. To address this issue, repair technologies for large-aperture optics are extensively employed. However, the operation of high-power laser system generates a large number of optics requiring repair. Currently, microscopic inspection is widely used for target points classification due to its high accuracy, but it has limitations such as small field of view and low efficiency. Utilizing the OTSU algorithm and Convolutional Neural Networks (CNN), a dark-field classification model for optical surface target points has been developed. Upon conducting experiments with several network models, the ResNet model, a probability threshold of 0.998 were determined. In conclusion, the classification accuracy for defects was 99.18% and for contaminants was 90.34%. The outcomes show that target points on the surfaces of optics can be accurately classified using this method. © 2024 SPIE.

关键词： Machine vision

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GCA-Net: A Global Context Aggregation Network for Effective Optical Flow 49

GCA-Net: A Global Context Aggregation Network for Effective ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Xie, Tao Gao, Jinghan Wang, Ke Li, Ruifeng Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350331820

Optical flow seeks to estimate the per-pixel 2D motion between two frames by identifying corresponding pixels. Current flow estimators typically involve per-pixel feature extraction, multi-scale 4D correlation volume construction, and iterative flow field updates through a Conv-GRU module. However, the locality of convolutional features in these methods renders the calculated correlations vulnerable to different noises. In addition, the Conv-GRU module of these methods is only executed with a convolution layer, which is incapable of exploiting context clues from larger window sizes even inside the image being queried itself, thus raising it more difficult for the model to process images with challenging regions, e.g., textureless areas. To this end, we introduce GCA-Net, a global context aggregation network for credible yet effective optical flow estimation. More specifically, we propose a highly efficient multi-scale transformer (MSFormer) layer which enables the per-pixel feature to aggregate long-range information from other features, hence building more accurate 4D correlation volumes. Besides, we develop an attention-enhanced Conv-GRU block (AttGRU) that can incorporate information alongside a larger context window even within itself empowering our network to estimate optical flow in even the most challenging regions. Experimentally, we demonstrate that GCA-Net outperforms previous state-of-the-art methods by large margins on Sintel (Final) and KITTI 2015 (background and foreground) benchmarks. © 2023 IEEE.

关键词： Optical flows

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Optimizing Dataset Configuration for Improving Convolutional Neural Networks Performance in Chest X-ray Image Classification 8

Optimizing Dataset Configuration for Improving Convolutional...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： He, Zengmin Ren, Yi Wang, Honggang Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350302455

Chest X-ray (CXR) is essential for physicians to diagnose lung diseases in clinical medicine. With the development of computer and deep learning techniques, creating CXR datasets to train convolutional neural networks (CNNs) has become a popular research topic. However, there are still challenges in creating datasets due to class imbalance and the ratio setting of datasets. This study investigated the impact of class imbalance and the ratio of training, validation, and test sets on CNNs classification performance by optimizing the dataset configuration. This was achieved by directly modifying the ratio, applying oversampling based on the adaptive contrast enhancement (ACE) algorithm, and random undersampling to balance the dataset classes, followed by modifying the ratio again. Therefore, seven datasets were obtained, which were utilized to individually train four CNNs based on transfer learning and fine-tuning techniques. Evaluation metrics based on the confusion matrix were utilized to demonstrate the enhanced classification performance of CNNs. The results indicated that at least 17% of the accuracy of CNNs trained by the dataset with modified ratios was improved as compared with the dataset with an unreasonable initial configuration. Additionally, the overall evaluation metrics of CNNs were further improved by balancing the dataset classes and modifying the ratios. ChexNet demonstrated the best classification performance among the four CNNs, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). Furthermore, ChexNet was trained by a class balanced dataset with a ratio of 7:2:1, resulting in the best evaluation metrics, including F1 Score, balanced accuracy, accuracy, recall, specificity, and precision, which were 97.81%, 97.78%, 97.78%, 98.73%, 96.84%, and 96.89%, respectively. Therefore, optimizing dataset configuration can effectively improve the performance of CNNs, providing empirical guidance for researchers in creating dat

关键词： Convolutional neural networks

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Dual-Arm Dynamic Planning with Considering Arm Reachability Constraint in Task Space 16th

Dual-Arm Dynamic Planning with Considering Arm Reachability ...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Shu, Xin Fan, Xinyang Min, Kang Ji, Zhu Ni, Fenglei Liu, Hong State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (纸本)9789819964888

This paper aims to address the issue of planning dual-arm motions in scenarios involving tracking dynamic desired pose and obstacle avoidance. In situations where dual-arm motion requires synchronous behavior, inflexible planning, encountering obstacles, and beyond-the-arm motion capability may lead to task failure. To overcome these issues, we propose a dynamic-system-based method for dual-arm collaborative planning. The method can coordinate the motions of dual arms while keeping synchronous behavior in tracking the moving target and avoiding obstacles. Meanwhile, we incorporate the reachability by modeling the motion boundary to ensure that the arms moving within the reachable space. The experiment successfully verified the above scenarios, showcasing its adaptability in dual-arm planning and its potential applicability in dual-arm applications such as transportation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Target tracking

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Smoke Attention Based Laparoscopic Image Desmoking Network with Hybrid Guided Embedding

Smoke Attention Based Laparoscopic Image Desmoking Network w...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Liu, Ziteng Gao, Wenpeng Zhu, Jiahua Liu, Bainan Fu, Yili School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150080 China

ISBN: (纸本)9781665481090

Surgical smoke can obscure the surgeon's line of sight during the laparoscopic procedure, potentially posing risk to the patients. Robot assisted-minimally invasive surgery (MIS) also faces such a challenge, which also hinders its autonomous operation. This paper proposes a desmoking method for laparoscopic surgery smoke removal. As the surgical smoke is hetergeneous, a two-stage network is developed to estimate the smoke distribution and reconstruct the corresponding smoke-free scene with the hybrid embedding guidance, including the estimated smoke mask and the initial image. The network is designed following the concept of the atmospheric scattering model, which makes the network more explainable. To qualitatively and quantitatively evaluate the proposed method, a synthetic laparoscopic dataset is generated and a real laparoscopic dataset is obtained. Experimental results show that the Peak Signal to Noise Ratio (PSNR) of the proposed method is 1.9% higher than that of the DehazeFormer, while the run-time is shorter more than 40.9%. The proposed method is comparable to or even outperforms the state-of-the-arts in desmoking quality and computation cost. © 2024 IEEE.

关键词： Laparoscopy

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Data Augmentation for Improving CNNs in Medical Image Classification 8

Data Augmentation for Improving CNNs in Medical Image Classi...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Ren, Yi He, Zengmin Deng, Yang Huang, Bo Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350302455

Medical image is essential for physicians to diagnose diseases. And convolutional neural networks (CNNs) have gained momentum for computer-aided diagnosis (CAD) medical image. However, there are still challenges in CNNs related to a lack of data and class-imbalanced datasets. Data augmentation is utilized to address the issues mentioned above. In this study, the Pseudo-color enhancement algorithm (OCEAN and TWILIGHT), common linear transform, CLAHE enhancement, and K-means clustering algorithm were applied to pneumonia X-ray images for data augmentation. Thus, five processed datasets were finally obtained. The results indicated that five data-augmentation methods effectively improved the performance of CNNs for the pneumonia X-ray images binary classification detection, in which the CLAHE enhancement and OCEAN enhancement methods had the accuracy and F1 Score with 97.42%, 97.19%, and 97.42%, 98.36%, respectively. DenseNet121 showed the best classification performance of four CNNs utilized in this study, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). To verify the generalizability of the two enhancement methods, CLAHE and OCEAN enhancement methods were applied to the Magnetic Resonance Imaging (MRI) dataset of Alzheimer's disease, which had the accuracy and F1 Score with 98.15% , 98.15%, and 97.22%, 97.68%, respectively. Therefore, these simple and efficient data-augmentation methods effectively improve the performance of CNNs for diagnosing medical image, which can provide theoretical reference for physicians to diagnose the above two diseases, and advance the application of clinical medicine. © 2023 IEEE.

关键词： Magnetic resonance imaging

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An Effective Rotor-Shape Optimization Method for IPM Motor with 1/2 Slot per Phase per Pole

An Effective Rotor-Shape Optimization Method for IPM Motor w...

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2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023

作者： Yu, Guodong Sun, Shuqi Li, Junlong Xiao, Lijun Xu, Yongxiang Zou, Jibin Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350301571

Although IPM motor with 1/2 slot per phase per pole has a relatively less rotor loss in comparison with other fractional slot concentrated winding (FSCW), the problems of THD of back-EMF and cogging torque are worse, which limits its application in electric vehicles and other industry fields. This paper proposes an effective rotor-shape optimization method to suppress both THD of back-EMF and cogging torque for improving torque ripple problem. Different from the prevalent rotor optimization methods, the proposed rotor-shape optimization method associates both shape function optimization of rotor surface with PM shaping, which can effectively decrease optimization parameters, and enhance optimization efficiency. To clarify the optimization strategy, the back-EMF and cogging torque for this PM motor with 1/2 slot per phase per pole are analyzed firstly. Then, the proposed optimization method is presented in detail. Finally, the optimized IPM motor is prototyped and its experimental results verifies the effectiveness of the proposed optimization method. © 2023 IEEE.

关键词： back-EMF cogging torque IPM motor optimization method

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Damage evolution and removal behaviors of GaN crystals involved in double-grits grinding

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International Journal of Extreme Manufacturing 2024年第2期6卷 469-484页

作者： Chen Li Yuxiu Hu Zongze Wei Chongjun Wu Yunfeng Peng Feihu Zhang Yanquan Geng State Key Laboratory of Robotics and System(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China Key Laboratory of Microsystems and Microstructures Manufacturing(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China College of Mechanical Engineering Donghua UniversityShanghai 201620People’s Republic of China Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005People’s Republic of China

Elucidating the complex interactions between the work material and abrasives during grinding of gallium nitride(GaN)single crystals is an active and challenging research *** this study,molecular dynamics simulations were performed on double-grits interacted grinding of GaN crystals;and the grinding force,coefficient of friction,stress distribution,plastic damage behaviors,and abrasive damage were systematically *** results demonstrated that the interacted distance in both radial and transverse directions achieved better grinding quality than that in only one *** grinding force,grinding induced stress,subsurface damage depth,and abrasive wear increase as the transverse interacted distance ***,there was no clear correlation between the interaction distance and the number of atoms in the phase transition and dislocation *** interacted distances between abrasives can decrease grinding force,coefficient of friction,grinding induced stress,subsurface damage depth,and abrasive wear during the grinding *** results of grinding tests combined with cross-sectional transmission electron micrographs validated the simulated damage results,*** atoms,high-pressure phase transition,dislocations,stacking faults,and lattice *** results of this study will deepen our understanding of damage accumulation and material removal resulting from coupling between abrasives during grinding and can be used to develop a feasible approach to the wheel design of ordered abrasives.

关键词： grinding double-grits molecular dynamics damage material removal gallium nitride

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